diff --git a/BUGS.md b/BUGS.md
new file mode 100644
index 0000000..63df50a
--- /dev/null
+++ b/BUGS.md
@@ -0,0 +1,6 @@
+ * For some reason, load(tidyverse) does not work correctly in the
+ environment seasnap-de. However, dplyr and other base tidyverse packages
+ load without issue.
+
+ * cluster profile doesn't work, but only when called from the pipeline.
+ Running the script interactively works well.
diff --git a/DE_pipeline.snake b/DE_pipeline.snake
index 91802d0..42b4980 100644
--- a/DE_pipeline.snake
+++ b/DE_pipeline.snake
@@ -64,11 +64,14 @@ def get_inputs_all():
 	#functional annotation
 	inputs.append(pph.expand_path(step = "goseq", extension = "go.rds",   if_set = dict(goseq=True) ))
 	inputs.append(pph.expand_path(step = "goseq", extension = "kegg.rds", if_set = dict(goseq=True) ))
-	inputs.append(pph.file_path(step = "annotation", extension = "rds", contrast="all"))
+	#inputs.append(pph.file_path(step = "annotation", extension = "rds", contrast="all"))
 	inputs.append(pph.file_path(step = "export_raw_counts", extension = "xlsx", contrast = "all"))
 	inputs.append(pph.expand_path(step = "cluster_profiler", extension = "rds", if_set = dict(cluster_profiler=dict(run=True)) ))
-	inputs.append(pph.file_path(step = "tmod_dbs", extension = "rds", contrast="all"))
-	inputs.append(pph.file_path(step = "tmod_pca", extension = "rds", contrast="all", if_set=dict(tmod_pca=True)))
+  # XXX uncomment the following line to run tmod_pca
+
+	if config["contrasts"]["defaults"]["tmod_pca"]:
+		inputs.append(pph.file_path(step = "tmod_pca", extension = "rds", contrast="all"))
+
 	inputs.append(pph.expand_path(step = "tmod", extension = "rds", if_set = dict(tmod=True)))
 
 	#time series
diff --git a/README.md b/README.md
index 08833ad..bad234c 100644
--- a/README.md
+++ b/README.md
@@ -46,21 +46,39 @@ Quick-Start
 After cloning this git repository:
 
 ```
-git clone git@cubi-gitlab.bihealth.org:CUBI/Pipelines/sea-snap.git
+git clone git@cubi-gitlab.bihealth.org:CUBI/Pipelines/seasnap-pipeline.git
 ```
 
 all required tools and packages can be installed via conda.
-Download and install them into a new environment called `sea_snap`:
+
+Currently there are two separate conda environments, one for the mapping
+pipeline and one for the DE pipeline
+
+Download and install them into new environments called `sea_snap_mapping`
+and `sea_snap_de`:
 
 ```
-conda env create -f conda_env.yaml
+conda env create -f conda_env_mapping.yaml
+conda env create -f conda_env_DE.yaml
 ```
 
-The file `conda_env.yaml` is located in the main directory of the git repository.
+The files `conda_env_mapping.yaml` and `conda_env_DE.yaml` are located in the main directory of the git repository.
 Each time before using SeA-SnaP, activate the environment with:
 
 ```
-conda activate sea_snap
+conda activate seasnap-mapping
+```
+
+or 
+```
+conda activate seasnap-de
+```
+
+Finally, run the following command in the seasnap-de environment:
+
+```
+conda activate seasnap-de
+Rscript install_r_packages.R
 ```
 
 ### Running the pipeline
@@ -90,7 +108,6 @@ The next steps depend on, whether you want to run:
 
 - [**`The mapping pipeline`**](documentation/run_mapping.md)
 - [**`The DE pipeline`**](documentation/run_DE.md)
-- [**`The sc pipeline`**](documentation/run_sc.md)
 
 The results of an analysis can also be [`exported`](documentation/export.md) to a new folder structure, e.g. to upload them to SODAR.
 
diff --git a/TODO.md b/TODO.md
index 55b1835..fca182e 100644
--- a/TODO.md
+++ b/TODO.md
@@ -2,5 +2,8 @@ The roadmap ahead:
 
 1) merging Eric's branches and the ATAC_seq branch
 2) making sure sea-snap runs smoothly with newer versions of snakemake (it
-doesn't currently)
-3) making the step from drmaa to cluster profiles.
+doesn't currently) --> DONE for mapping pipeline if snakemake version = 7.19.1
+3) making the step from drmaa to cluster profiles --> mostly DONE for mapping pipeline 
+4) optimizing resource requirements in `mapping_pipeline.snake` (check `mem` vs `mem_per_cpu`) and adding them to `DE_pipeline.snake`
+5) allowing sample-specific indices for bwa / salmon / kallisto?
+6) adapting the `conda_env.yaml` files
diff --git a/cluster_config_drmaa.json b/cluster_config_drmaa.json
index 03e7a6f..4852c23 100644
--- a/cluster_config_drmaa.json
+++ b/cluster_config_drmaa.json
@@ -33,7 +33,7 @@
 
     "salmon":
     {
-        "h_vmem": "4000",
+         "h_vmem": "4000",
         "h_rt": "40:00:00",
         "pe": "8"
     },
@@ -108,19 +108,12 @@
         "pe": "4"
     },
 
-    "cellranger_count":
-    {
-        "h_vmem": "4000",
-        "h_rt": "40:00:00",
+    "cluster_profiler":
+    {   "h_vmem": "20000",
+        "h_rt": "10:00:00",
         "pe": "1"
-    },
-
-    "velocyto_run":
-    {
-        "h_vmem": "20000",
-        "h_rt": "40:00:00",
-        "pe": "8"
     }
+    
 }
 
 
diff --git a/cluster_config_slurm.json b/cluster_config_slurm.json
index 80823d7..49526b8 100644
--- a/cluster_config_slurm.json
+++ b/cluster_config_slurm.json
@@ -3,7 +3,7 @@
     {
         "snake_opt": "-j 100 -k --restart-times 0 --max-jobs-per-second 5 --rerun-incomplete",
 
-        "run_command": "--profile \"cubi-v1\""
+        "run_command": "--profile \"cubi-dev\""
     },
     
     "__default__":
@@ -19,15 +19,15 @@
 
     "star":
     {
-        "mem": "20000M",
-        "time": "40:00:00",
+        "mem": "60000M",
+        "time": "8:00:00",
         "cpus-per-task": 8
     },
 
     "star_index":
     {
-        "mem": "20000M",
-        "time": "40:00:00",
+        "mem": "40000M",
+        "time": "8:00:00",
         "cpus-per-task": 8
     },
 
@@ -120,6 +120,35 @@
         "mem": "20000M",
         "time": "40:00:00",
         "cpus-per-task": 8
+    },
+    "preseq_lc_extrap":
+    {
+        "mem": "40000M",
+        "time": "40:00:00",
+        "cpus-per-task": 8
+    },
+    "preseq_c_curve":
+    {
+        "mem": "40000M",
+        "time": "40:00:00",
+        "cpus-per-task": 8
+    },
+    "tmod_dbs":
+    {
+        "mem": "16000M",
+        "time": "8:00:00",
+        "cpus-per-task": 8
+    },
+
+    "cluster_profiler":
+    {
+        "mem": "8000M",
+        "time": "4:00:00",
+        "cpus-per-task": 8
     }
+
+
 }
 
+
+
diff --git a/conda_env.yaml b/conda_env_DE.yaml
similarity index 68%
rename from conda_env.yaml
rename to conda_env_DE.yaml
index 498f1ab..7a46865 100644
--- a/conda_env.yaml
+++ b/conda_env_DE.yaml
@@ -1,35 +1,13 @@
-name: sea_snap
+name: seasnap-de
 channels:
-  - bioconda
   - conda-forge
+  - bioconda
   - defaults
 dependencies:
-  - python
-  - r
-
-  - bamtools
-  - bedtools
-  - fastqc
-  - macs2
-  - multiqc
-  - picard
-  - preseq
-  - qualimap
-  - rna-seqc
-  - rsa
-  - rsem
-  - rseqc
-  - salmon
-  - samtools
-  - sqlite
-  - star
-  - subread
-  - tpmcalculator
-  - trimadap
-  - vim
-  - rpy2
-
-  - bioconductor-deseq2
+  - python>=3.9
+  - snakemake=7.19
+  - r-base>=4.1
+  - bioconductor-deseq2=1.38
   - bioconductor-genomicfeatures
   - bioconductor-annotationdbi
   - bioconductor-org.hs.eg.db # annotation for human
@@ -37,7 +15,6 @@ dependencies:
   - bioconductor-tximport
   - bioconductor-goseq
   - bioconductor-apeglm
-  - bioconductor-dupradar
   - bioconductor-biomart
   - bioconductor-enrichplot
   - bioconductor-clusterprofiler
@@ -48,7 +25,6 @@ dependencies:
   - bioconductor-rtracklayer
   - r-blob
   - r-cairo
-  - r-cellranger
   - r-cowplot
   - r-crayon
   - r-devtools
@@ -57,20 +33,26 @@ dependencies:
   - r-ggplotify
   - r-readr
   - r-readxl
+  - r-writexl
   - r-roxygen2
   - r-tidyr
   - r-tidyselect
   - r-testthat
+  - r-remotes
   - r-ashr
   - r-pheatmap
   - r-shiny
-  - r-msigdbr
+  - r-msigdbr>=7.4
   - r-dplyr
   - r-biocmanager
   - r-xml2
   - r-xopen
-
+  - r-tmod>=0.50.11
+# Required for the actual report
+  - r-dt
+  - r-purrr
+  - r-plotly
+  - r-pander
+  - bioconductor-vsn
+  - r-tidyverse
   - drmaa
-  - snakemake
-
-
diff --git a/conda_env_mapping.yaml b/conda_env_mapping.yaml
new file mode 100644
index 0000000..cd9cdb4
--- /dev/null
+++ b/conda_env_mapping.yaml
@@ -0,0 +1,28 @@
+name: seasnap-mapping
+channels:
+  - conda-forge
+  - bioconda
+  - defaults
+dependencies:
+  - python>=3.9
+  - snakemake=7.19
+  - bamtools
+  - bedtools
+  - fastqc
+  - macs2
+  - multiqc
+  - picard
+  - preseq
+  - qualimap
+  - rna-seqc
+  - rsem
+  - salmon
+  - samtools=1.16
+  - sqlite
+  - star=2.7.3a
+  - subread=2.0
+  - trimadap
+  - drmaa
+  - bioconductor-dupradar
+  - rseqc
+  - bwa
diff --git a/defaults/sc_config_defaults.yaml b/defaults/sc_config_defaults.yaml
deleted file mode 100644
index 6852f44..0000000
--- a/defaults/sc_config_defaults.yaml
+++ /dev/null
@@ -1,67 +0,0 @@
-#---------------------------------------- general pipeline parameters
-pipeline_param:
-  # adjust pattern of stored files
-  out_path_pattern: sc_analysis/{step}/{sample}.{mate}/out/{step}.{sample}.{mate}.{extension}
-  log_path_pattern: sc_analysis/{step}/{sample}.{mate}/report/{step}.{sample}.{mate}.{extension}
-  in_path_pattern: ../input/{sample}/{sample}.{mate}
-
-  test_config: true
-  report_snippets: ""
-
-  feature_ref: ""
-  cellranger_executable: "cellranger"  # default assuming cellranger is in the PATH
-
-  # adjust which results are produced
-  produce_results:
-    - cellranger
-    - velocyto
-
-  input_choice:
-    velocyto:
-      - cellranger_count
-      - cellranger_aggr
-
-#---------------------------------------- organism annotation
-organism_defaults: null
-
-#---------------------------------------- parameters for rules
-rule_options:
-  cellranger_count:
-    cmd_opt: ""   # "--jobmode sge --maxjobs=100 --jobinterval=1000"
-  velocyto_run:
-    cmd_opt: "--samtools-memory 4000 -@ 4"
-
-#---------------------------------------- parameters for the jupyter notebook
-jupyter_notebook:
-  snippet_parameters: {}
-  defaults: {}
-  report_snippets:
-    - load_matrix.ipynb
-    - filter_and_normalize.ipynb
-    - plot_dim_reduction.ipynb
-    - ranking_and_marker_genes.ipynb
-    - compute_velocities.ipynb
-
-#---------------------------------------- configuration for export
-export:
-  blueprint:
-    file: SODAR_export_blueprint.txt
-    command: |
-      imkdir -p $(dirname {dest} )
-      irsync -a -K {src} i:{dest}
-  path_pattern:
-    - __SODAR__/{sample}/%Y_%m_%d_{files:cellranger}
-    - __SODAR__/{sample}/%Y_%m_%d_cellranger/{files:cellranger_logs}.tgz
-    - __SODAR__/{sample}/%Y_%m_%d_{files:velocyto}/velocyto.{sample}.loom
-  cellranger:
-    - dir: {step: cellranger_count, mate: all_mates}
-      suffix: "cellranger_wd/{sample}/outs"
-      compress: tar
-      compress_list: [analysis, raw_feature_bc_matrix, filtered_feature_bc_matrix]
-  cellranger_logs:
-    - dir: {step: cellranger_count, mate: all_mates}
-      suffix: "cellranger_wd/{sample}"
-      compress: tar
-      exclude: ["{sample}/outs", "{sample}/SC_RNA_COUNTER_CS"]
-  velocyto:
-    - files: {step: velocyto_run, extension: loom, mate: all_mates}
diff --git a/defaults/sc_config_ranges.yaml b/defaults/sc_config_ranges.yaml
deleted file mode 100644
index ee4b67d..0000000
--- a/defaults/sc_config_ranges.yaml
+++ /dev/null
@@ -1,47 +0,0 @@
-#---------------------------------------- general pipeline parameters
-pipeline_param:
-  out_path_pattern: \S+
-  log_path_pattern: \S+
-  in_path_pattern: \S+
-
-  cellranger_executable: \S+
-  feature_ref: .*
-  test_config: {__opt__: [true, false]}
-
-#---------------------------------------- organism annotation
-organism_defaults:
-  __opt__: [null, \S*]
-
-#---------------------------------------- parameters for rules
-rule_options:
-  cellranger_count:
-    cmd_opt: .*
-  velocyto_run:
-    cmd_opt: .*
-        
-#---------------------------------------- configuration for export
-export:
-  blueprint:
-    __opt__:
-      - null
-      - file: \S*
-        command: .+
-  path_pattern: [\S+]
-  __any__:
-    - __opt__:
-        - files:
-            __any_other__:
-              step: \S+
-              extension: \S+
-              log: {__opt__: [true, false]}
-        - dir:
-            __any_other__:
-              step: \S+
-              log: {__opt__: [true, false]}
-      __any_other__:
-        compress:
-          __opt__: [zip, tar]
-
-
-
-
diff --git a/documentation/prepare_input.md b/documentation/prepare_input.md
index 26b58f6..6a1991f 100644
--- a/documentation/prepare_input.md
+++ b/documentation/prepare_input.md
@@ -98,6 +98,8 @@ Feel free to extend the config file and push it back to gitlab. In this way the
 
 For an explanation how to export to SODAR see [`SODAR export`](export.md).
 
+**Note: to use sample-specific STAR indices, add entries `star_index: /path/to/star_index/` (careful: must be compatible with STAR version in the pipeline!) or `genome: /path/to/genome.fa` and `gtf: /path/to/gtf` for auto-creation to the `sample_info.yaml`**
+
 ---
 
 [Back](../README.md) to main doc.
diff --git a/documentation/quickstart.md b/documentation/quickstart.md
index 00996d1..37e9212 100644
--- a/documentation/quickstart.md
+++ b/documentation/quickstart.md
@@ -73,18 +73,19 @@
     * edit other options and parameters to your taste, but basically you
       ready to go.
 
- 4. Generate the file `samples.info` using the command `sea-snap.py sample_info`
+ 4. Generate the file `sample_info.yaml` using the command `sea-snap.py sample_info`
 
     * If you have a custom extension to your read files, then use the
       `--add_ext` option.
     * A common problem is that the `in_path_pattern` defined in the
       `mapping_config.yaml` file does not match the actual file paths. 
     * After successfully running this step, make sure that the
-      automatically generated `samples.info` file is correct.
+      automatically generated `sample_info.yaml` file is correct.
 
  5. Run the pipeline with `./sea-snap mapping l` on a local machine or
-    `./sea-snap mapping c` on the computing cluster. To run on SLURM nodes,
-    run `./sea-snap mapping --slurm c`.
+    `./sea-snap mapping c` on the computing cluster. 
+    
+    To run using SGE scheduler, run `./sea-snap mapping --sge c` (deprecated; check DRMAA config)
  
  6. So, where is the report? Where is the QC? Just take a look at
     `mapping/multiqc/all_samples.all_mates/out/multiqc.all_samples.all_mates.qc_report.html`,
diff --git a/documentation/run_sc.md b/documentation/run_sc.md
deleted file mode 100644
index 1e10dc9..0000000
--- a/documentation/run_sc.md
+++ /dev/null
@@ -1,60 +0,0 @@
-[Back](../README.md) to main doc.
-
----
-
-Run single cell analysis
------------
-
-### 1) download files (from SODAR)
-
-First, make sure you have the following files accessible (or download them from SODAR):
-
-- fastq files
-- ISA-tab files
-- feature reference (if some samples used feature barcoding)
-
-Note: The ISA-tab assay file should contain the columns **Parameter Value[Library name mRNA]** and **Parameter Value[Library name sample tag]**.
-`Library name sample tag` is only filled, when feature barcoding was used for a sample.
-Samples with and without feature barcodes can be mixed.
-
-### 2) edit the config file
-
-After creating a [working directory](../README.md#running-the-pipeline)
-
-```
-path/to/sea-snap working_dir
-```
-
-edit the config file:
-
-```
-vim sc_config.yaml
-```
-
-Set the **in_path_pattern** to the fastq files and the **transcriptome** as well as **gtf** files for [CellRanger](https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/installation) that are in the reference package.
-If the experiment used feature barcoding, set the path to the [**Feature Reference CSV**](https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/feature-bc-analysis).
-
-### 3) create a sample info file
-
-This extracts information from the fastq file paths about the samples using the [in_path_pattern](prepare_input.md).
-
-The ISA-tab assay file can also be used to extract meta-information about the samples.
-It should contain columns **Parameter Value[Library name mRNA]** and **Parameter Value[Library name sample tag]**.
-
-```
-./sea-snap sample_info --from sodar --input <a_isa_assay_file> --config_files sc_config.yaml
-```
-
-### 4) run the pipeline
-
-```
-./sea-snap sc --slurm c
-```
-
-### 5) create a jupyter notebook from snippets
-
-(this is under development; feel free to edit and add snippets)
-
-```
-./sea-snap sc l create_ipynb
-```
\ No newline at end of file
diff --git a/external_scripts/tmod_functions.R b/external_scripts/tmod_functions.R
index 3fd6f83..cb2220a 100644
--- a/external_scripts/tmod_functions.R
+++ b/external_scripts/tmod_functions.R
@@ -4,7 +4,8 @@ library(glue)
 #' Volcano plots with ggplot
 ggvolcano <- function(lfc, pvals, symbol=NULL, xlim=NULL, ylim=NULL, pval.thr=.05, lfc.thr=1) {
 
-  require(tidyverse)
+  require(dplyr)
+  require(purrr)
   require(ggplot2)
 
   p.t <- pval.thr
@@ -52,7 +53,8 @@ tmod_filter_format_res <- function(res, pval.thr=.05, AUC.thr=.65) {
 
   if(is.null(res)) { return(res) }
 
-  require(tidyverse)
+  require(dplyr)
+  require(purrr)
   require(DT)
 
   res <- res %>% 
diff --git a/install_r_packages.R b/install_r_packages.R
new file mode 100644
index 0000000..af7270f
--- /dev/null
+++ b/install_r_packages.R
@@ -0,0 +1 @@
+remotes::install_github("bihealth/orthomapper")
diff --git a/mapping_pipeline.snake b/mapping_pipeline.snake
index 388cf0c..121a109 100644
--- a/mapping_pipeline.snake
+++ b/mapping_pipeline.snake
@@ -72,9 +72,8 @@ def get_inputs_all():
 	# mapping results
 	mapping_choices = config["pipeline_param"]["mapping_results"]
 	if "star-gene_counts" in mapping_choices: 
-		inputs += pph.expand_path("star",           "bam",            fix="!sample")
+		inputs += pph.expand_path("star",	    "bam",	      fix="!sample")
 		inputs += pph.expand_path("feature_counts", "feature_counts", fix="!sample")
-		inputs += pph.expand_path("tpm_calculator", "tsv",            fix="!sample")
 	if "salmon-transcript_counts" in mapping_choices: 
 		inputs += pph.expand_path("salmon", "sf", fix="!sample")
 	if "ciri-circRNA" in mapping_choices:
@@ -88,9 +87,9 @@ def get_inputs_all():
 	if "fastqc" in qc_choices: 
 		inputs += pph.expand_path("fastqc", "zip_names.txt")
 	if "star-gene_counts" in mapping_choices: 
-		if "dupradar"         in qc_choices: 
+		if "dupradar"	      in qc_choices: 
 			inputs += pph.expand_path("dupradar", "done", fix="!sample")
-		if "rna_seqc"         in qc_choices: 
+		if "rna_seqc"	      in qc_choices: 
 			inputs += pph.expand_path("rna_seqc", "done", fix="!sample")
 		if "preseq_lc_extrap" in qc_choices: 
 			inputs += pph.expand_path("preseq_lc_extrap", "future_yield.txt", fix="!sample")
@@ -102,7 +101,7 @@ def get_inputs_all():
 			inputs += pph.expand_path("qualimap_bamqc",   "done", fix="!sample")
 		if "infer_experiment" in qc_choices: 
 			inputs += pph.expand_path("infer_experiment", "strand_stat.txt", fix="!sample")
-		if "qc"               in qc_choices: 
+		if "qc"		      in qc_choices: 
 			inputs += pph.expand_path("qc", "done", fix="!sample")
 		if "bw_from_bam"      in qc_choices:
 			inputs += pph.expand_path("bw_from_bam", "bw", fix="!sample")
@@ -129,9 +128,9 @@ rule all:
 		quality_control = "".join(["- {}\n".format(qc) for qc in config["pipeline_param"]["QC_results"]])
 		loctime = asctime(localtime(time()))
 		rule_execution = pph.file_path("pipeline_report", "rule_execution.png", fix="all")
-		summary        = pph.file_path("pipeline_report", "summary.csv",        fix="all")
-		version_info   = pph.file_path("pipeline_report", "version_info.txt",   fix="all")
-		conda_info     = pph.file_path("pipeline_report", "conda_info.txt",     fix="all")
+		summary        = pph.file_path("pipeline_report", "summary.csv",	fix="all")
+		version_info   = pph.file_path("pipeline_report", "version_info.txt",	fix="all")
+		conda_info     = pph.file_path("pipeline_report", "conda_info.txt",	fix="all")
 		dag = rule_execution.split("/")[-1]
 		shell("conda list > {}".format(version_info))
 		shell("conda info > {}".format(conda_info))
@@ -198,9 +197,11 @@ rule fastqc:
 	log:
 		out  = pph.file_path(step="fastqc", extension="output.log", log=True)
 	params:
-		outdir  = pph.out_dir_name(step="fastqc")
-	threads:
-		2
+		outdir	= pph.out_dir_name(step="fastqc")
+	threads: 2
+	resources:
+		mem_mb=4000,
+		h_rt="24:00:00"
 	run:
 		reads = " ".join(input)
 		
@@ -225,8 +226,8 @@ rule fastqc:
 
 rule star_index:
 	input:
-		genome = config["organism"]["files"]["genome"],
-		gtf    = config["organism"]["files"]["gtf"]
+		genome = lambda wildcards: config["organism"]["files"]["genome"] if wildcards.sample=="all_samples" else config["sample_info"][wildcards.sample]["genome"],
+		gtf = lambda wildcards: config["organism"]["files"]["gtf"] if wildcards.sample=="all_samples" else config["sample_info"][wildcards.sample]["gtf"]
 	output:
 		index = pph.out_dir_name(step = "star_index")+"/SA"
 	log:
@@ -234,6 +235,9 @@ rule star_index:
 	params:
 		options = config["rule_options"]["star_index"]["cmd_opt"]
 	threads: 8
+	resources:
+		mem_mb=64000,
+		h_rt="24:00:00"
 	run:
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -249,15 +253,35 @@ rule star_index:
 		script_file = pph.log(log.out, snakemake_format(script), step="star_index", extension="sh", **wildcards)
 		shell("bash '{script_file}' &>> '{log.out}'")
 
+
+def get_star_index (wildcards):
+	"""get star index or compute one for all or specific samples"""
+	# if there's a sample-specific star index (precomputed)
+	if "star_index" in config["sample_info"][wildcards.sample]:
+		#print("using pre-computed star index for "+wildcards.sample)
+		return config["sample_info"][wildcards.sample]["star_index"] + "/SA"
+	# if there's a sample-specific genome and gtf
+	elif "genome" in config["sample_info"][wildcards.sample] and "gtf" in config["sample_info"][wildcards.sample]:
+		#print("using newly computed star index for "+wildcards.sample)
+		return pph.out_dir_name(step = "star_index", fix="!sample", sample = wildcards.sample) + "/SA"
+	# otherwise
+	else:
+		if "star_index" in config["organism"] and config["organism"]["star_index"] is not None:
+			#print("using pre-computed global star index for "+wildcards.sample)
+			return config["organism"]["star_index"] + "/SA"
+		else:
+			#print("using newly computed global star index for "+wildcards.sample)
+			return pph.out_dir_name(step = "star_index", fix="all") + "/SA"
+
 rule star:
 	input:
-		index = pph.out_dir_name(step = "star_index", fix="all")+"/SA",
+		index = get_star_index,
 		reads1 = lambda wildcards: pph.get_fastq_pairs(wildcards, mate_key="paired_end_extensions", mate=0),
 		reads2 = lambda wildcards: pph.get_fastq_pairs(wildcards, mate_key="paired_end_extensions", mate=1) #identical if unstranded
 	output:
-		bam         =      pph.file_path(step="star", extension="bam"),
+		bam	    =	   pph.file_path(step="star", extension="bam"),
 		usrt_bam    = temp(pph.file_path(step="star", extension="unsorted.bam")),
-		gene_counts =      pph.file_path(step="star", extension="gene_counts.tab")
+		gene_counts =	   pph.file_path(step="star", extension="gene_counts.tab")
 	log:
 		out = pph.file_path(step="star", extension="output.log", log=True)
 	params:
@@ -265,6 +289,9 @@ rule star:
 		options = config["rule_options"]["star"]["cmd_opt"],
 		trim = True if config["rule_options"]["star"]["trim"]=="yes" else False
 	threads: 16
+	resources:
+		mem_mb=48000,
+		h_rt="24:00:00"
 	run:
 		# prepare read input
 		reads = ",".join(input.reads1)
@@ -314,7 +341,7 @@ rule star:
 		mv {params.outdir}/Aligned.out.bam {output.usrt_bam}
 		
 		#----- mark duplicates
-		picard MarkDuplicates I={output.bam} O={params.outdir}/{wildcards.sample}.mdup.bam M={params.outdir}/{wildcards.sample}.metrics.out TMP_DIR={params.outdir}
+		picard -Xmx48G MarkDuplicates I={output.bam} O={params.outdir}/{wildcards.sample}.mdup.bam M={params.outdir}/{wildcards.sample}.metrics.out TMP_DIR={params.outdir}
 		mv {params.outdir}/{wildcards.sample}.mdup.bam {output.bam}
 
 		#----- generate BAM index (.bai)
@@ -339,6 +366,9 @@ rule bw_from_bam:
 		pph.file_path(step="bw_from_bam", extension="bw")
 	log:
 		out = pph.file_path(step="bw_from_bam", extension="output.log", log=True)
+	resources:
+		mem_mb=32000,
+		h_rt="4:00:00"
 	run:
 		genome_size=config["organism"]["genome_size"]
 		script = textwrap.dedent(r"""
@@ -367,6 +397,9 @@ rule macs2:
 		pn=pph.file_path(step="macs2", extension="peaks.narrowPeak")
 	log:
 		out = pph.file_path(step="macs2", extension="output.log", log=True)
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		genome_abbr=config["organism"]["abbreviation"]
 		script = textwrap.dedent(r"""
@@ -389,35 +422,6 @@ rule macs2:
 
 
 
-
-
-
-
-rule tpm_calculator:
-	input:
-		bam = pph.file_path(step="star", extension="bam"),
-		gtf = config["organism"]["files"]["gtf"]
-	output:
-		pph.file_path(step="tpm_calculator", extension="tsv")
-	log:
-		out = pph.file_path(step="tpm_calculator", extension="output.log", log=True)
-	params:
-		nsrt_bam = pph.file_path(step="tpm_calculator", extension="name_sorted.bam")
-	run:
-		script = textwrap.dedent(r"""
-		#----- prepare
-		set -eux
-		TPMCalculator -version || true
-
-		#----- run TPMCalculator
-		TPMCalculator -g {input.gtf} -b {input.bam}
-		cut -f1,7 $(basename {input.bam} .bam)_genes.out > {output}
-		mv $(basename {input.bam} .bam)_genes.* $(dirname {output})
-		""")
-
-		script_file = pph.log(log.out, snakemake_format(script), step="tpm_calculator", extension="sh", **wildcards)
-		shell("bash '{script_file}' &>> '{log.out}'")
-
 ##-------------------- bwa ---------------------------------------------------------------------------------
 
 GENOME_FILE_NAME = os.path.basename(config["organism"]["files"]["genome"])
@@ -433,6 +437,9 @@ rule bwa_index:
 		out = pph.file_path(step="bwa_index", extension="output.log", log=True)
 	params:
 		options = config["rule_options"]["bwa_index"]["cmd_opt"]
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		db_prefix = os.path.join(output.index, GENOME_FILE_NAME)
 		
@@ -468,6 +475,9 @@ rule bwa:
 		trim = True if config["rule_options"]["bwa"]["trim"]=="yes" else False,
 		run_stats = "true" if config["rule_options"]["bwa"]["run_stats"] else "false"
 	threads: 8
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		db_prefix = os.path.join(params.index_dir, GENOME_FILE_NAME)
 
@@ -530,6 +540,9 @@ rule ciri:
 		sam = pph.file_path(step="ciri", extension="sam"),
 		options = config["rule_options"]["ciri"]["cmd_opt"]
 	threads: 8
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		samtools_threads = threads//2
 
@@ -560,6 +573,9 @@ rule generate_transcriptome:
 	log:
 		out = pph.file_path(step = "generate_transcriptome", extension="output.log", log=True)
 	threads: 8
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -577,13 +593,16 @@ rule generate_transcriptome:
 rule salmon_index:
 	input:
 		transcriptome = pph.out_dir_name(step = "generate_transcriptome")+"/transcriptome.fa",
-		genome        = config["organism"]["files"]["genome"]
+		genome	      = config["organism"]["files"]["genome"]
 	output:
 		index = pph.out_dir_name(step = "salmon_index")+"/pos.bin"
 	log:
 		out = pph.file_path(step = "salmon_index", extension="output.log", log=True)
 	params:
 		options = config["rule_options"]["salmon_index"]["cmd_opt"]
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -622,6 +641,9 @@ rule salmon:
 		options = config["rule_options"]["salmon"]["cmd_opt"],
 		trim = True if config["rule_options"]["salmon"]["trim"]=="yes" else False
 	threads: 8
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		# prepare read input and trimming
 		unpaired = input.reads1 == input.reads2
@@ -664,11 +686,14 @@ rule feature_counts:
 		out = pph.file_path(step="feature_counts", extension="output.log", log=True)
 	params:
 		nsrt_bam = pph.file_path(step="feature_counts", extension="name_sorted.bam"),
-                options = config["rule_options"]["feature_counts"]["cmd_opt"]
+		options = config["rule_options"]["feature_counts"]["cmd_opt"]
 	threads: 2
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		protocol = {"unstranded":0, "forward":1, "reverse":2}[config["sample_info"][wildcards.sample]["stranded"]]
-		paired   = "-p" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
+		paired	 = "-p" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
 		
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -699,9 +724,12 @@ rule dupradar:
 	log:
 		out = pph.file_path(step="dupradar", extension="output.log", log=True)
 	threads: 8
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		protocol = {"unstranded":0, "forward":1, "reverse":2}[config["sample_info"][wildcards.sample]["stranded"]]
-		paired  = "TRUE" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else "FALSE"
+		paired	= "TRUE" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else "FALSE"
 		
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -733,6 +761,9 @@ rule infer_experiment:
 		pph.file_path(step="infer_experiment", extension="strand_stat.txt")
 	log:
 		out = pph.file_path(step="infer_experiment", extension="output.log", log=True)
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -754,8 +785,11 @@ rule preseq_lc_extrap:
 		pph.file_path(step="preseq_lc_extrap", extension="future_yield.txt")
 	log:
 		out = pph.file_path(step="preseq_lc_extrap", extension="output.log", log=True)
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
-		paired   = "-P -l 10000000" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
+		paired	 = "-P" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
 		
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -776,8 +810,11 @@ rule preseq_c_curve:
 		pph.file_path(step="preseq_c_curve", extension="complexity.txt")
 	log:
 		out = pph.file_path(step="preseq_c_curve", extension="output.log", log=True)
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
-		paired   = "-P -l 10000000" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
+		paired	 = "-P" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
 		
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -803,10 +840,11 @@ rule qualimap_rnaseq:
 	log:
 		out = pph.file_path(step="qualimap_rnaseq", extension="output.log", log=True)
 	resources:
-		mem_mb = 24000
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		protocol = {"unstranded":"non-strand-specific", "forward":"strand-specific-forward", "reverse":"strand-specific-reverse"}[config["sample_info"][wildcards.sample]["stranded"]]
-		paired   = "-pe" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
+		paired	 = "-pe" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else ""
 		
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -834,7 +872,8 @@ rule qualimap_bamqc:
 	log:
 		out = pph.file_path(step="qualimap_bamqc", extension="output.log", log=True)
 	resources:
-		mem_mb = 24000
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		protocol = {"unstranded":"non-strand-specific", "forward":"strand-specific-forward", "reverse":"strand-specific-reverse"}[config["sample_info"][wildcards.sample]["stranded"]]
 		
@@ -865,6 +904,9 @@ rule collapse_annotation:
 		pph.file_path(step="collapse_annotation", extension="genes.gtf")
 	log:
 		out = pph.file_path(step="collapse_annotation", extension="output.log", log=True)
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	run:
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -885,11 +927,14 @@ rule rna_seqc:
 		touch(pph.file_path(step="rna_seqc", extension="done"))
 	log:
 		out = pph.file_path(step="rna_seqc", extension="output.log", log=True)
+	resources:
+		mem_mb=32000,
+		h_rt="24:00:00"
 	params:
 		options = config["rule_options"]["rna_seqc"]["cmd_opt"]
 	run:
 		protocol = {"unstranded":"", "forward":"--stranded=FR", "reverse":"--stranded=RF"}[config["sample_info"][wildcards.sample]["stranded"]]
-		paired   = "" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else "--unpaired"
+		paired	 = "" if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else "--unpaired"
 		
 		script = textwrap.dedent(r"""
 		#----- prepare
@@ -918,6 +963,9 @@ rule qc:
 		touch(pph.file_path(step="qc", extension="done"))
 	log:
 		out = pph.file_path(step="qc", extension="output.log", log=True)
+	resources:
+		mem_mb=4000,
+		h_rt="4:00:00"
 	run:
 		paired = '' if len(config["sample_info"][wildcards.sample]["paired_end_extensions"])>1 else '-e'
 		
@@ -942,8 +990,11 @@ rule multiqc:
 	output:
 		pph.file_path(step="multiqc", extension="qc_report.html")
 	log:
-		out            = pph.file_path(step="multiqc", extension="output.log",        log=True),
+		out	       = pph.file_path(step="multiqc", extension="output.log",	      log=True),
 		multiqc_config = pph.file_path(step="multiqc", extension="multiqc_conf.yaml", log=True)
+	resources:
+		mem_mb=4000,
+		h_rt="4:00:00"
 	run:
 		# compile multiqc config
 		multiqc_dict = config["report"]["multiqc"]
@@ -978,6 +1029,9 @@ rule circRNA_report:
 		get_inputs_all()
 	output:
 		pph.file_path("circRNA_report", "Rmd", sample="all_samples", flowcell="all_flowcells", lane="all_lanes", mate="all_mates", library="all_libraries")
+	resources:
+		mem_mb=4000,
+		h_rt="4:00:00"
 	run:
 		rt = ReportTool(pph, profile="circRNA")
 		report_text = rt.generate_report()
@@ -989,7 +1043,7 @@ rule circRNA_report:
 			pph.log_generated_files(save_to=file_table, path_pattern=path)
 			id_suffix, _ = rt.get_id_suffix(tag, num)
 			text_sub["file_tab"] += (f'file_tab{id_suffix} <- data.frame(read.table("{file_table}", sep="\\t", header=TRUE))\n'
-			                         f'file_tab{id_suffix}$filename <- as.character(file_tab{id_suffix}$filename)\n')
+						 f'file_tab{id_suffix}$filename <- as.character(file_tab{id_suffix}$filename)\n')
 			text_sub["config"]   += f'config{id_suffix} <- yaml.load_file("{config_file}")\n'
 
 		report_text = report_text.replace("{{WORKING_DIRECTORY}}", os.getcwd() + os.sep)
diff --git a/sc_config.yaml b/sc_config.yaml
deleted file mode 100644
index e73c3c3..0000000
--- a/sc_config.yaml
+++ /dev/null
@@ -1,31 +0,0 @@
-#--- organism annotation
-
-organism_defaults: ### FILL HERE ###  (e.g. Homo_sapiens.yaml)
-
-organism:
-  __options__: [name, genus, taxon, files, star_index, salmon_index, R]
-  ### OVERWRITE ###  organism defaults (e.g. gtf, genome and indices)
-  files:
-    cellranger_transcriptome: ""   ### FILL HERE ###  (the transcriptome to use with CellRanger)
-    cellranger_gtf: ""   ### FILL HERE ###  (the gtf to use with CellRanger)
-
-
-#--- general pipeline parameters
-
-pipeline_param:
-  __options__: [out_path_pattern, log_path_pattern, in_path_pattern, feature_ref]
-  
-  in_path_pattern: ### FILL HERE ###  (path pattern where fastq files are stored)
-
-  feature_ref: ""  ### FILL HERE ###  (if feature barcoding was used)
-
-
-#--- parameters for rules
-
-rule_options:
-  __options__: [cellranger_count, velocyto_run]
-
-
-#--- parameters for the jupyter notebook
-jupyter_notebook:
-  __options__: [snippet_parameters, defaults, report_snippets]
\ No newline at end of file
diff --git a/sc_pipeline.snake b/sc_pipeline.snake
deleted file mode 100644
index e08fac7..0000000
--- a/sc_pipeline.snake
+++ /dev/null
@@ -1,319 +0,0 @@
-## SeA-SnaP single cell pipeline for RNA-seq analysis
-## version: 0.1
-## author: J.P.Pett (patrick.pett@bihealth.de)
-
-import os, sys, yaml, re, textwrap, pandas as pd
-import tools.pipeline_tools
-from collections import OrderedDict
-from time import asctime, localtime, time
-from pathlib import Path
-from snakemake.utils import report, format as snakemake_format, min_version
-from snakemake.logging import logger
-from tools.pipeline_tools import MappingPipelinePathHandler, ReportTool
-
-min_version("3.7")
-shell.prefix("set -e  pipefail;")
-tools.pipeline_tools.warnings.simplefilter("always")
-yaml.add_representer(OrderedDict, lambda dumper, data: dumper.represent_dict(dict(data)))
-
-# source files
-SNAKEDIR  = Path(workflow.current_basedir)
-SNAKEFILE = workflow.snakefile
-SCRIPTDIR = str(SNAKEDIR / "external_scripts")
-
-# assemble config
-config_file_name = config["file_name"] if "file_name" in config else "sc_config.yaml"
-configfile: str(SNAKEDIR / "defaults" / "sc_config_defaults.yaml")
-configfile: config_file_name
-configfile: "sample_info.yaml"
-if config["organism_defaults"]:
-	configfile: str(SNAKEDIR / "defaults" / config["organism_defaults"])
-	configfile: config_file_name
-
-# create path handler
-conf_ranges = str(SNAKEDIR / "defaults" / "sc_config_ranges.yaml")
-test_config = conf_ranges if config["pipeline_param"]["test_config"] else None
-pph = MappingPipelinePathHandler(workflow, test_config)
-
-# link indices
-pph.link_index(step="cellranger_count", fix="all", subdir="outdir", add_done=True)
-
-# exclude symbols '.' and '/' from wildcards
-wildcard_constraints: 
-	sample="[^./]+",
-	mate  ="[^./]+"
-
-onstart:
-	# draw a dag
-	dag_file = pph.file_path(step="pipeline_report", extension="rule_execution.png", fix="all")
-	os.makedirs(os.path.dirname(dag_file), exist_ok=True)
-	shell("snakemake --quiet --snakefile {} --rulegraph | dot -Tpng > {}".format(SNAKEFILE, dag_file))
-	# info about the pipeline run
-	info_file = pph.file_path(step="pipeline_report", extension="summary.csv", fix="all")
-	os.makedirs(os.path.dirname(info_file), exist_ok=True)
-	shell("snakemake --quiet --snakefile {} --summary | sed 's/\t/, /g' > {}".format(SNAKEFILE, info_file))
-	# save merged config
-	config_file = pph.file_path(step="pipeline_report", extension="yaml", fix="all")
-	with open(config_file, "w") as f: yaml.dump(config, f, default_flow_style=False)
-
-##-------------------- starting point ----------------------------------------------------------------------
-
-def get_inputs_all():
-	inputs = []
-
-	results = config["pipeline_param"]["produce_results"]
-	if "velocyto" in results:
-		if config["pipeline_param"]["input_choice"]["velocyto"][0] == "cellranger_aggr":
-			inputs += [pph.file_path("velocyto_run", "loom", fix="all")]
-		else:
-			inputs += pph.expand_path(step="velocyto_run", extension="loom", fix="!sample")
-	elif "cellranger-aggr" in results:
-		inputs += [pph.file_path(step="cellranger_aggr", extension="done", fix="all")]
-	elif "cellranger" in results:
-		inputs += pph.expand_path(step="cellranger_count", extension="done", fix="!sample")
-
-	return inputs
-
-
-shell("rm -f {}".format(pph.file_path(step="pipeline_report", extension="report.html", fix="all")))
-
-rule all:
-	input:
-		get_inputs_all()
-	output:
-		html = pph.file_path(step="pipeline_report", extension="report.html", fix="all")
-	run:
-		loctime = asctime(localtime(time()))
-		rule_execution = pph.file_path("pipeline_report", "rule_execution.png", fix="all")
-		summary        = pph.file_path("pipeline_report", "summary.csv",        fix="all")
-		version_info   = pph.file_path("pipeline_report", "version_info.txt",   fix="all")
-		conda_info     = pph.file_path("pipeline_report", "conda_info.txt",     fix="all")
-		dag = rule_execution.split("/")[-1]
-		shell("conda list > {}".format(version_info))
-		shell("conda info > {}".format(conda_info))
-		report("""
-		===========================
-		RNAseq single cell pipeline
-		===========================
-		
-		**Finished: {loctime}**
-		
-		.. image:: {dag}
-		
-		File status at pipeline start:
-		==============================
-		
-		.. csv-table::
-			:file: {summary}
-			
-		Version info:
-		=============
-		
-		.. include:: {version_info}
-			:literal:
-		
-		Conda info:
-		===========
-		
-		.. include:: {conda_info}
-			:literal:
-		
-		""", output.html, graph = rule_execution, table = summary)
-		
-rule export:
-	input:
-		get_inputs_all()
-	run:
-		pph.export()
-
-##-------------------- CellRanger -------------------------------------------------------------------------------
-
-rule cellranger_count:
-    """ run cellranger count """
-	input:
-		reads = lambda wildcards: pph.get_fastq_pairs(wildcards, mate="*"),
-		transcriptome = config["organism"]["files"]["cellranger_transcriptome"]
-	output:
-		outdir = directory(pph.out_dir_name(step="cellranger_count")+"/cellranger_wd"),
-		links  = directory(pph.out_dir_name(step="cellranger_count")+"/input_links"),
-		done = touch(pph.file_path(step="cellranger_count", extension="done"))
-	log:
-		out = pph.file_path(step = "cellranger_count", extension="output.log", log=True)
-	params:
-		options = config["rule_options"]["cellranger_count"]["cmd_opt"],
-		feature_ref = config["pipeline_param"]["feature_ref"],
-		cellranger_exec = config["pipeline_param"]["cellranger_executable"]
-	run:
-		# using feature barcodes ?
-		feature_ref = str(Path(params.feature_ref).resolve()) if params.feature_ref else ""
-
-		# create libraries file
-		lib_file_content = ["fastqs, sample, library_type"]
-		prefixes = [p for p, t in config["sample_info"][wildcards.sample]["lib_types"]]
-		pref_dup = len(prefixes) != len(set(prefixes))
-		for lpref, ltype in config["sample_info"][wildcards.sample]["lib_types"]:
-			for lp in lpref.split(","):
-				# in some cases the same prefix is annotated in ISA tab for feature and GEX
-				# in this case use the trick of duplicating links to fastqs and
-				# adding tag_ to the prefix
-				if pref_dup and ltype != "Gene Expression":
-					lib_file_content.append(f"{Path(output.links).resolve()}, tag_{lp}, {ltype}")
-				else:
-					lib_file_content.append(f"{Path(output.links).resolve()}, {lp}, {ltype}")
-		pref_dup = "true" if pref_dup else "false"
-		lib_file_content = "\n".join(lib_file_content)
-
-		script = textwrap.dedent(r"""
-		#----- prepare
-		set -eux
-		{params.cellranger_exec} --version || true
-
-		#----- collect fastq input links
-		mkdir {output.links}
-		ln -sf $(readlink -f {input.reads}) {output.links}
-		# if names are the same for feature and GEX fastqs,
-		# duplicate links with different name:
-		if {pref_dup}; then
-		  for f in {output.links}/*; do
-		    cp -av "$f" "$(dirname $f)/tag_$(basename $f)"
-		  done
-		fi
-
-		#----- Cellranger counting
-		mkdir -p {output.outdir}; cd {output.outdir}; ls -lh
-		#-- write libraries file
-		cat << 'EOF' > "libraries.csv"
-		{lib_file_content}
-		EOF
-		#-- link feature barcodes if present
-		feature_ref="{feature_ref}"
-		if [ "$feature_ref" ]; then
-		  ln -sf $feature_ref "feature_ref.csv"
-		  feature_ref="--feature-ref=feature_ref.csv"
-		fi
-		#-- run cellranger count
-		{params.cellranger_exec} count --id="{wildcards.sample}" --libraries="libraries.csv" $feature_ref --transcriptome={input.transcriptome} {params.options}
-		cd -
-		""")
-
-		script_file = pph.log(log.out, snakemake_format(script), step="cellranger_count", extension="sh", **wildcards)
-		shell("bash '{script_file}' &>> '{log.out}'")
-
-
-rule cellranger_aggr:
-	input:
-		pph.expand_path(step="cellranger_count", extension="done", fix="mate")
-	output:
-		outdir = directory(pph.out_dir_name(step="cellranger_aggr")+"/cellranger_wd"),
-		done = touch(pph.file_path(step="cellranger_aggr", extension="done"))
-	log:
-		out = pph.file_path(step = "cellranger_aggr", extension="output.log", log=True)
-	params:
-	    cellranger_exec = config["pipeline_param"]["cellranger_executable"]
-	run:
-		aggr_csv_content = ["library_id, molecule_h5"]
-		for count_results in input:
-			sample_name = pph.wildcard_values_from(count_results, False)["sample"][0]
-			mol_info = Path(count_results).parent / "cellranger_wd" / sample_name / "outs" / "molecule_info.h5"
-			aggr_csv_content.append(f"{sample_name}, {str(mol_info.resolve())}")
-		aggr_csv_content = "\n".join(aggr_csv_content)
-
-		script = textwrap.dedent(r"""
-		#----- prepare
-		set -eux
-		{params.cellranger_exec} --version || true
-
-		#----- Cellranger counting
-		mkdir -p {output.outdir}; cd {output.outdir}
-		#-- write libraries file
-		cat << 'EOF' > "output_aggr.csv"
-		{aggr_csv_content}
-		EOF
-		#-- run cellranger aggr
-		{params.cellranger_exec} aggr --id="cellranger_dir" --csv="output_aggr.csv"
-		cd -
-		""")
-
-		script_file = pph.log(log.out, snakemake_format(script), step="cellranger_aggr", extension="sh", **wildcards)
-		shell("bash '{script_file}' &>> '{log.out}'")
-
-##-------------------- Velocyto -------------------------------------------------------------------------------
-
-rule velocyto_run:
-	""" run velocyto on 10X Chromium samples """
-	input:
-		gtf = config["organism"]["files"]["cellranger_gtf"],
-		cellranger_done = pph.choose_input(
-			choice_name = "velocyto",
-			options = [
-				dict(step = "cellranger_aggr",  extension = "done"),
-				dict(step = "cellranger_count", extension = "done")
-			]
-		)
-	output:
-		pph.file_path(step="velocyto_run", extension="loom")
-	log:
-		out = pph.file_path(step="velocyto_run", extension="output.log", log=True)
-	params:
-		cellranger_outdir = pph.choose_input(
-			choice_name = "velocyto",
-			func = lambda **kw: os.path.join(pph.out_dir_name(**kw),"cellranger_wd",kw["sample"],"outs"),
-			options = [
-				dict(step = "cellranger_aggr"),
-				dict(step = "cellranger_count")
-			]
-		),
-		mask = config["organism"]["files"]["velocyto_mask_gtf"],
-		options = config["rule_options"]["velocyto_run"]["cmd_opt"]
-	run:	
-		mask = f"-m {params.mask}" if params.mask else ""
-
-		script = textwrap.dedent(r"""
-		#----- prepare
-		set -eux
-		velocyto --version
-
-		#----- run velocyto
-		#velocyto run10x \
-		#{params.cellranger_outdir} \
-		#{input.gtf} \
-		#{params.options}
-		velocyto run -b {params.cellranger_outdir}/filtered_feature_bc_matrix/barcodes.tsv.gz {mask} -o $(dirname {output}) {params.options} {params.cellranger_outdir}/possorted_genome_bam.bam {input.gtf}
-
-		#----- move results
-		mv $(dirname {output})/*.loom {output}
-		""")
-
-		script_file = pph.log(log.out, snakemake_format(script), step="velocyto_run", extension="sh", **wildcards)
-		shell("bash '{script_file}' &>> '{log.out}'")
-
-##-------------------- jupyter nb -------------------------------------------------------------------------------
-
-rule create_ipynb:
-	""" compile a jupyter notebook for second line analysis """
-	input:
-		get_inputs_all()
-	output:
-		pph.file_path("create_ipynb", "ipynb", fix="all")
-	run:
-		rt = ReportTool(pph, profile="sc_analysis")
-		report_text = rt.generate_report()
-
-		text_sub = dict(file_tab="", config="")
-		for tag, num, path in ((tag, num, path) for tag, paths in rt.use_results.items() for num, path in enumerate(paths)):
-			file_table  = pph.file_path("create_ipynb",  "tsv", fix="all", path_pattern=path)
-			config_file = pph.file_path("pipeline_report", "yaml", fix="all", path_pattern=path)
-			pph.log_generated_files(save_to=file_table, path_pattern=path)
-
-			id_suffix, _ = rt.get_id_suffix(tag, num)
-			text_sub["file_tab"] += f'file_tab{id_suffix} = pd.read_csv("{file_table}", sep="\\t")\n'
-			text_sub["config"]   += (
-				f'with open("{config_file}", "r") as stream:\n'
-				f'\tconfig{id_suffix} = yaml.safe_load(stream)\n'
-			)
-
-		report_text = report_text.replace("{{WORKING_DIRECTORY}}", os.getcwd() + os.sep)
-		report_text = report_text.replace("{{LOAD_FILE_TABLE}}", text_sub["file_tab"])
-		report_text = report_text.replace("{{LOAD_CONFIG_FILE}}", text_sub["config"])
-
-		with open(output[0], "w") as f: f.write(report_text)
\ No newline at end of file
diff --git a/sea-snap.py b/sea-snap.py
index 3114e07..8c96cff 100755
--- a/sea-snap.py
+++ b/sea-snap.py
@@ -14,7 +14,6 @@
 CONFIGS = dict(
 	DE="DE_config.yaml",
 	mapping="mapping_config.yaml",
-	sc="sc_config.yaml",
 )
 
 CLUSTER_CONFIG = dict(
@@ -171,7 +170,7 @@ def rmdir(dir_name):
 					item.unlink()
 			dir_path.rmdir()
 
-	rmdir("cluster_log")
+	rmdir("logs")
 	for p in Path(".").glob("temp_snakemake*.sh"): p.unlink()
 	for p in Path(".").glob("run_pipeline.sh"): p.unlink()
 	for p in Path(".").glob("core.*"): p.unlink()
@@ -196,7 +195,7 @@ def run_pipeline(snakefile, args):
 		method = args.submit
 		with open(CLUSTER_CONFIG[method], "r") as json_file:
 			data = json.load(json_file)
-		Path("cluster_log").mkdir(exist_ok=True)
+		#Path("cluster_log").mkdir(exist_ok=True)
 		run_script = Path("run_pipeline.sh")
 		s_command  = "#!/bin/bash\nsnakemake --snakefile {sfile}".format(sfile = str(SCRIPT_DIR / snakefile))
 		if args.snake_options: s_command += " " + " ".join(args.snake_options)
@@ -223,13 +222,6 @@ def run_DE_pipeline(args):
 	run_pipeline("DE_pipeline.snake", args)
 
 
-def run_sc_pipeline(args):
-	"""
-	run single cell pipeline
-	"""
-	run_pipeline("sc_pipeline.snake", args)
-
-
 ############################## DEFINE PARSER
 
 parser = argparse.ArgumentParser(description="run SeA-SnaP pipelines and helpers")
@@ -240,7 +232,7 @@ def run_sc_pipeline(args):
 #--- parser for setup_working_directory
 parser_working_dir = subparsers.add_parser('working_dir', help="setup a working directory for running the pipeline")
 parser_working_dir.add_argument('--dirname', '-d',   default="results_%Y_%m_%d/", help="name of directory")
-parser_working_dir.add_argument('--configs', '-c', nargs='+', default=["mapping", "DE", "sc"], choices=["mapping", "DE", "sc"], help="configs to be imported")
+parser_working_dir.add_argument('--configs', '-c', nargs='+', default=["mapping", "DE"], choices=["mapping", "DE"], help="configs to be imported")
 parser_working_dir.set_defaults(func=setup_working_directory)
 
 #--- parser for generate_sample_info
@@ -308,7 +300,6 @@ def run_sc_pipeline(args):
 parser_cleanup_log = subparsers.add_parser('cleanup_log', help="delete log files from cluster execution")
 parser_cleanup_log.set_defaults(func=cleanup_cluster_log)
 
-
 ############################## PARSE ARGUMENTS
 
 if len(sys.argv)==1:
diff --git a/tools/ISAtab_parse_conf.yaml b/tools/ISAtab_parse_conf.yaml
index a9d3575..f13819a 100644
--- a/tools/ISAtab_parse_conf.yaml
+++ b/tools/ISAtab_parse_conf.yaml
@@ -29,10 +29,3 @@ instrument:
   value:
     ".*illumina.*": "\\g<0>"
 
-lib_types:
-  columns:
-    - "Parameter Value\\[Library name mRNA\\]"
-    - "Parameter Value\\[Library name sample tag\\]"
-  value:
-    ".*": {"\\g<0>": "\\col_mode: Parameter Value[Library name mRNA]:Gene Expression,Parameter Value[Library name sample tag]:Antibody Capture"}
-  add: true
\ No newline at end of file
diff --git a/tools/pipeline_tools.py b/tools/pipeline_tools.py
index c03274a..b96e805 100644
--- a/tools/pipeline_tools.py
+++ b/tools/pipeline_tools.py
@@ -1445,7 +1445,6 @@ def update_sample_info(self, library_default="unstranded", add=False):
 			if comb.sample not in sample_info:
 				sample_info[comb.sample] = {"stranded": library_default, "read_extension": comb.read_extension}
 				sample_info[comb.sample]["paired_end_extensions"] = [getattr(comb, "mate", "")]
-				sample_info[comb.sample]["lib_types"] = {comb.lib_type: None} if hasattr(comb, "lib_type") else {}
 			else:
 				if hasattr(comb, "mate"):
 					paired_end_ext = getattr(comb, "mate", "")
@@ -1457,14 +1456,6 @@ def update_sample_info(self, library_default="unstranded", add=False):
 					if paired_end_ext not in paired_end_ext_lst:
 						paired_end_ext_lst.append(paired_end_ext)
 						paired_end_ext_lst.sort()
-				if hasattr(comb, "lib_type"):
-					lib_types = sample_info[comb.sample]["lib_types"]
-					if lib_types == {}:
-						raise ValueError(
-							"Error compiling sample information: sample {} has names with and without library type information".format(
-								comb.lib_type))
-					if comb.lib_type not in lib_types:
-						lib_types[comb.lib_type] = None
 		if add:
 			# add missing fields
 			self._add_info_fields(sample_info)